OSCR

Competing programs shape cortical sensorimotor-association axis development.

Code ↔ Paper

8 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 8 matches · 4 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Association and sensorimotor gene module curation ↔ GM.cal.func.R, lines 21–99 · score 0.95 · edgeR, filterByExpr, normalizeCounts, tweeDEseq, RNentropy, module gene
  2. [2] § Methods › Association and sensorimotor gene module curation ↔ 01_get_GM_list.R, the whole file · a weak match · score 0.88 · RNentropy, exon microarray, module gene, RNA seq, limma, shared genes
  3. [3] § Emerging signatures along developing S–A axis ↔ 05_macaque_plot_heatmap.R, the whole file · a weak match · score 0.68 · RNA seq, gene modules, HIP, macaque, VFC, IPC
  4. [4] § Emerging signatures along developing S–A axis ↔ 05_macaque_plot_heatmap.R, the whole file · a weak match · score 0.65 · RNA seq, gene module, heatmaps, HIP, prenatal, macaque
  5. [5] § Emerging signatures along developing S–A axis ↔ 06_cortical_disease_enrichment.R, lines 48–62 · score 0.63 · RNA seq, sub, HIP, VFC, IPC, enrichment
  6. [6] § Methods › Analysis of human cerebral organoid data ↔ 03_plot_organoid_ExN_dual_color_FeaturePlot.R, lines 63–111 · score 0.63 · AddModuleScore, GAD1, organoid, Cell, gene
  7. [7] § Emerging signatures along developing S–A axis ↔ 02_plot_heatmap.R, the whole file · a weak match · score 0.56 · gene module, heatmaps, HIP, microarray, prenatal, VFC
  8. [8] § Methods › Disease gene enrichment analysis ↔ 06_cortical_disease_enrichment.R, lines 64–105 · score 0.55 · genes associated, diseases, lupus, ADHD, enrichment

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

R · 75 lines · 3.1 KB · no license · 2 matches

  1. ###################################################################
  2. # Time: 2025-08-15 15:33:55 EDT #
  3. # Author: Xinyun LI #
  4. # Email: [email hidden] #
  5. # Description: This script includes functions to plot #
  6. # normal/distorted heatmaps of #
  7. # gene modules using macaque micro-array data #
  8. ###################################################################
  10. library(tidyverse)
  11. library(readxl)
  12. library(cowplot)
  13. source("./macaque.plot.func.R")
  15. outdir.heatmap <- paste0("outs/heatmap")
  16. if(!dir.exists(outdir.heatmap)){
  17. dir.create(outdir.heatmap,recursive = T)
  18. }
  20. # prepare data
  21. rs.order <- rev(c('OFC','MFC','DFC','VFC','M1C','S1C','IPC','V1C','A1C','STC', 'ITC','AMY', "HIP"))
  22. # load data
  23. ## zhu18_monkey
  24. fpkm_zhu18 <- read.table('PATH_TO_Zhu2018_RNA_seq_data/nhp_development_RPKM_rmTechRep.txt',header = T) %>%
  25. mutate(Geneid = rownames(.))
  26. meta_zhu18 <- readRDS('data/meta.zhu2018.rds',header = T) %>%
  27. dplyr::filter(Regioncode %in% rs.order)
  30. # load GM
  31. gm.dir <- "outs/Final_GM"
  32. fname <- "shared"
  33. print(fname)
  34. df <- openxlsx::read.xlsx(paste0(gm.dir, "/",fname,".prenatal.GM.xlsx"))%>%
  35. dplyr::filter(Type%in%c("Af","At","Af n At","S"))%>%
  36. mutate(Type=factor(Type, levels=c("Af","At","Af n At","S")))%>%arrange(Type)
  37. module.gene.list <- split(df$GeneSymbol, df$Type)
  39. # plotting #################
  40. ## normal heatmap p4 to p9
  41. n.hp.gm <- plot.GM.normal.heatmap.p4to9.zhu18(
  42. module.gene.list=module.gene.list,
  43. rs.order=rs.order,
  44. zhu18.expr=fpkm_zhu18,
  45. zhu18.meta=meta_zhu18)
  46. n.n.gm=length(n.hp.gm)
  47. pdf(paste0(outdir.heatmap, "/EF2b_",fname,".p4to9.normal.heatmap.pdf"), width = 6.8*n.n.gm, height = 6)
  48. n.hp.gm.merge = plot_grid(plotlist = n.hp.gm, ncol = 4)
  49. print(n.hp.gm.merge)
  50. dev.off()
  52. ## normal heatmap p4 to p9 without smoothening
  53. n.hp.gm <- plot.GM.normal.heatmap.p4to9.zhu18.nosmooth(
  54. module.gene.list=module.gene.list,
  55. rs.order=rs.order,
  56. zhu18.expr=fpkm_zhu18,
  57. zhu18.meta=meta_zhu18)
  58. n.n.gm=length(n.hp.gm)
  59. pdf(paste0(outdir.heatmap, "/EF2b_",fname,".p4to9.normal.heatmap.nosmooth.pdf"), width = 6.8*n.n.gm, height = 6)
  60. n.hp.gm.merge = plot_grid(plotlist = n.hp.gm, ncol = 4)
  61. print(n.hp.gm.merge)
  62. dev.off()
  64. ## normal heatmap p4 to p9 without smoothening
  65. n.hp.gm <- plot.GM.normal.heatmap.p4to9.zhu18.nosmooth.noimpute(
  66. module.gene.list=module.gene.list,
  67. rs.order=rs.order,
  68. zhu18.expr=fpkm_zhu18,
  69. zhu18.meta=meta_zhu18)
  70. n.n.gm=length(n.hp.gm)
  71. pdf(paste0(outdir.heatmap, "/EF2b_",fname,".p4to9.normal.heatmap.nosmooth.noimpute.pdf"), width = 6.8*n.n.gm, height = 6)
  72. n.hp.gm.merge = plot_grid(plotlist = n.hp.gm, ncol = 4)
  73. print(n.hp.gm.merge)
  74. dev.off()

05_macaque_plot_heatmap.R at commit 08389d1, no license · at the source

Overview

Authors: Jeremiah Tsyporin1, Menglei Zhang1, Cai Qi1, Ashlea Segal1,2, Xinyun Li1, Hyojin Kim1, Sang-Hun Choi1, Ivan Pavlovic1, Sara Bandiera1, Thomas Finn3, Suel-Kee Kim1, Akemi Shibata1, Takumi Nakamura1, Kohei Onishi4, Ziqin Zhang5,6, Elijah Hammarlund1, Graham Su1, Nikkita Salla1, Joy Kachko1, Christi Hawley1
and 18 other authorsShuiyu Li1, Daniel Z Doyle1,7, Xueyan Peng8, Timothy Nottoli9, Nuria Ruiz-Reig10, Fadel Tissir10,11, Yasushi Nakagawa12, Erica Herzog8, Shaojie Ma13, Kevin Gobeske1, Kartik Pattabiraman1,2,7, Tomomi Shimogori4, Alvaro Duque1, Alex Fornito14,15, Hao Huang5,6, Mikihito Shibata1, Bin Chen3, Nenad Sestan1,2,7,9,16,17,18,19,20
ORCID iDs: Menglei Zhang, Cai Qi, Xinyun Li, Hyojin Kim, Ivan Pavlovic, Sara Bandiera, Thomas Finn, Suel-Kee Kim, Akemi Shibata, Kohei Onishi, Ziqin Zhang, Nikkita Salla, Joy Kachko, Daniel Z Doyle, Timothy Nottoli, Nuria Ruiz-Reig, Fadel Tissir, Yasushi Nakagawa, Shaojie Ma, Alex Fornito, Hao Huang, Bin Chen, Nenad Sestan
20 affiliations
  1. Department of Neuroscience, Yale School of Medicine, New Haven, CT USA
  2. Wu Tsai Institute, Yale University, New Haven, CT USA
  3. Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, CA USA
  4. Laboratory for Molecular Mechanisms of Brain Development, Center for Brain Science, RIKEN, Wako, Japan
  5. Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA USA
  6. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA USA
  7. Yale Child Study Center, Yale School of Medicine, New Haven, CT USA
  8. Department of Medicine (Pulmonary Critical Care and Sleep), Yale School of Medicine, New Haven, CT USA
  9. Yale Genome Editing Center, Yale School of Medicine, New Haven, CT USA
  10. Laboratory of Developmental Neurobiology, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
  11. College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
  12. Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN USA
  13. Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
  14. Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria Australia
  15. Monash Biomedical Imaging, Monash University, Melbourne, Victoria Australia
  16. Department of Psychiatry, New Haven, CT USA
  17. Department of Comparative Medicine, Yale University, New Haven, CT USA
  18. Department of Genetics, Yale University, New Haven, CT USA
  19. Kavli Institute for Neuroscience, Yale University, New Haven, CT USA
  20. Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale University, New Haven, CT USA
Institutions: Yale University (United States); University of California, Santa Cruz (United States); RIKEN Center for Brain Science (Japan); RIKEN (Japan); Children's Hospital of Philadelphia (United States); University of Pennsylvania (United States); UCLouvain (Belgium); Hamad bin Khalifa University (Qatar); University of Minnesota (United States); Center for Excellence in Brain Science and Intelligence Technology (China); University of Chinese Academy of Sciences (China); Monash University (Australia)
Journal: Nature, volume 656, issue 8128, pages 688-699
Dates: received 8 May 2025; accepted 22 May 2026; published online 1 July 2026; in print 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41586-026-10699-x · PMID 42386980 · PMCID PMC13489954 · OpenAlex W4411716892
Open access: hybrid, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.06.26.660775
Status: code verified
Categories: human (organism), mouse (organism), autism (population)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Spectral & time-frequency, Evoked potentials, fMRI & imaging, Machine learning
Keywords: Molecular neuroscience, Signalling gradients, Neural patterning, Neural circuits
MeSH: Cerebral Cortex*, Models, Neurological*, Sensorimotor Cortex*, Animals, Autistic Disorder, Axon Guidance, Axons, Gene Expression Regulation, Developmental, Humans, Mice, Neocortex, Neurodevelopment, Semaphorins, Synapses, Tretinoin, Wnt Signaling Pathway (* major topic)
Topic: Neurogenesis and neuroplasticity mechanisms (Developmental Neuroscience, Neuroscience), according to OpenAlex
Funding: Simons Foundation
Citations: cited by 2 papers (Europe PMC); 139 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 8 matches between paragraphs and lines of code.

danjgale/surfplot

License: BSD-3-Clause
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 60c50008bcd0f58e1c132cb7d70aab9151911925, 18 November 2025
Languages: Python (22), Jupyter (8)
Size: 133 files, 30 scripts
Software Heritage: archived
Found in: the text, “Individual gene module PCA”
Holds: README, license file, environment (pyproject.toml, requirements.txt, docs/requirements.txt), documentation, 8 notebooks
Not found: CITATION.cff, tests, continuous integration
Tools: neuromaps (21 files), BrainSpace (9 files), Matplotlib (8 files), NumPy (7 files), NiBabel (4 files), Nilearn (3 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
32 files
At the source: github.com/danjgale/surfplot/tree/main

sestanlab/MIND

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 08389d1a2836bd473485eafc2440308f80807bc8, 3 May 2026
Languages: R (9)
Size: 12 files, 9 scripts
Software Heritage: not archived
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (9 files), cowplot (3 files), ggplot2 (2 files), data.table (1 file), edgeR (1 file), limma (1 file), patchwork (1 file), Seurat (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
9 files
At the source: github.com/sestanlab/MIND

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41586-026-10699-x.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 39 scripts, each with its path and the digest of its content;
  • 8 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41586-026-10699-x.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Publisher: n/a → Nature Portfolio
  • Funding: added Simons Foundation

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 38 authors, 4 keywords, 16 MeSH terms, 135 references.

Cite

This paper

Tsyporin, J., Zhang, M., Qi, C., Segal, A., Li, X., Kim, H., Choi, S.-H., Pavlovic, I., Bandiera, S., Finn, T., Kim, S.-K., Shibata, A., Nakamura, T., Onishi, K., Zhang, Z., Hammarlund, E., Su, G., Salla, N., Kachko, J., . . . Sestan, N. (2026). Competing programs shape cortical sensorimotor-association axis development. Nature, 656(8128), 688-699. https://doi.org/10.1038/s41586-026-10699-x

BibTeX

@article{tsyporin2026competing,
author = {Tsyporin, Jeremiah and Zhang, Menglei and Qi, Cai and Segal, Ashlea and Li, Xinyun and Kim, Hyojin and Choi, Sang-Hun and Pavlovic, Ivan and Bandiera, Sara and Finn, Thomas and Kim, Suel-Kee and Shibata, Akemi and Nakamura, Takumi and Onishi, Kohei and Zhang, Ziqin and Hammarlund, Elijah and Su, Graham and Salla, Nikkita and Kachko, Joy and Hawley, Christi and Li, Shuiyu and Doyle, Daniel Z and Peng, Xueyan and Nottoli, Timothy and Ruiz-Reig, Nuria and Tissir, Fadel and Nakagawa, Yasushi and Herzog, Erica and Ma, Shaojie and Gobeske, Kevin and Pattabiraman, Kartik and Shimogori, Tomomi and Duque, Alvaro and Fornito, Alex and Huang, Hao and Shibata, Mikihito and Chen, Bin and Sestan, Nenad},
title = {{Competing programs shape cortical sensorimotor-association axis development}},
journal = {Nature},
year = {2026},
month = jul,
volume = {656},
number = {8128},
pages = {688--699},
publisher = {Nature Portfolio},
issn = {0028-0836},
doi = {10.1038/s41586-026-10699-x},
url = {https://doi.org/10.1038/s41586-026-10699-x},
pmid = {42386980},
pmcid = {PMC13489954}
}

RIS

TY - JOUR
AU - Tsyporin, Jeremiah
AU - Zhang, Menglei
AU - Qi, Cai
AU - Segal, Ashlea
AU - Li, Xinyun
AU - Kim, Hyojin
AU - Choi, Sang-Hun
AU - Pavlovic, Ivan
AU - Bandiera, Sara
AU - Finn, Thomas
AU - Kim, Suel-Kee
AU - Shibata, Akemi
AU - Nakamura, Takumi
AU - Onishi, Kohei
AU - Zhang, Ziqin
AU - Hammarlund, Elijah
AU - Su, Graham
AU - Salla, Nikkita
AU - Kachko, Joy
AU - Hawley, Christi
AU - Li, Shuiyu
AU - Doyle, Daniel Z
AU - Peng, Xueyan
AU - Nottoli, Timothy
AU - Ruiz-Reig, Nuria
AU - Tissir, Fadel
AU - Nakagawa, Yasushi
AU - Herzog, Erica
AU - Ma, Shaojie
AU - Gobeske, Kevin
AU - Pattabiraman, Kartik
AU - Shimogori, Tomomi
AU - Duque, Alvaro
AU - Fornito, Alex
AU - Huang, Hao
AU - Shibata, Mikihito
AU - Chen, Bin
AU - Sestan, Nenad
TI - Competing programs shape cortical sensorimotor-association axis development
T2 - Nature
J2 - Nature
PY - 2026
DA - 2026/07/01
VL - 656
IS - 8128
SP - 688
EP - 699
SN - 0028-0836
PB - Nature Portfolio
DO - 10.1038/s41586-026-10699-x
UR - https://doi.org/10.1038/s41586-026-10699-x
LA - en
ER -

CSL-JSON

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